As social circumstances are changing, such as deterioration of public security, there is a growing need for grasping a congestion degree of a crowd from video of a surveillance camera to secure safety or relieve congestion. In video of a surveillance camera installed at a place where the height is restricted, such as an inside of a building, the installation height or the depression angle is limited, and the congestion degree needs to be grasped based on the assumption that persons are overlapped with each other in the screen. In this case, the number of persons cannot be counted one by one, and a method in which the congestion degree is calculated based on the relation between a feature in an image, such as the number of corners or an edge amount in the image, and the number of persons, is used as disclosed in PTL 1.
PTL 1 discloses that an approximate number of persons can be estimated from the number of corners as information related to the congestion degree, and congestion degree calculation unit holds a table associating the number of corners with the estimated number of persons to obtain the congestion degree.
PTL 2 discloses a method for measuring an escalator carrying load which includes steps of capturing a moving image from a camera, periodically sampling a still image from an input image, extracting a region to be measured from a cut-out still image, measuring an area of an image indicating a person in a photographed image, obtaining a regression coefficient from the area of the image indicating the person and the number of persons counted by a user from the same still image, and obtaining an area of an image indicating a person from each of a plurality of images periodically sampled, adding the areas of the images indicating of the person in each of the images, and calculating a total escalator carrying load based on the added area value and the regression coefficient.